Introducing Data Science: Big Data, Machine Learning, and more, using Python tools
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Introducing Data Science: Big Data, Machine Learning, and more, using Python tools
Introducing Data Science: Big Data, Machine Learning, and more, using Python tools
แƒ”แƒ แƒ—แƒ”แƒฃแƒšแƒ˜แƒก #: 4065022

Introducing Data Science: Big Data, Machine Learning, and more, using Python tools

แƒ”แƒ แƒ—แƒ”แƒฃแƒšแƒ˜แƒก #: 4065022

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แฒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ˜แƒก แƒแƒฆแƒฌแƒ”แƒ แƒ˜แƒšแƒแƒ‘แƒ

Shop Introducing Data Science: Big Data, Machine Learning, and more, using Python tools online at a best price in Georgia. 1633430030
  • SummaryIntroducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science.About the TechnologyMany companies need developers with data science skills to work on projects ranging from social media marketing to machine learning. Discovering what you need to learn to begin a career as a data scientist can seem bewildering. This book is designed to help you get started.About the BookIntroducing Data ScienceIntroducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. Youโ€™ll explore data visualization, graph databases, the use of NoSQL, and the data science process. Youโ€™ll use the Python language and common Python libraries as you experience firsthand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it. This book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, youโ€™ll have the solid foundation you need to start a career in data science.Whatโ€™s InsideHandling large dataIntroduction to machine learningUsing Python to work with dataWriting data science algorithmsAbout the ReaderThis book assumes you're comfortable reading code in Python or a similar language, such as C, Ruby, or JavaScript. No prior experience with data science is required.About the AuthorsDavy Cielen, Arno D. B. Meysman, and Mohamed Ali are the founders and managing partners of Optimately and Maiton, where they focus on developing data science projects and solutions in various sectors.Table of ContentsData science in a big data worldThe data science processMachine learningHandling large data on a single computerFirst steps in big dataJoin the NoSQL movementThe rise of graph databasesText mining and text analyticsData visualization to the end user
Publisher Manning
Publication date May 23, 2016
Edition First Edition
Language English
Print length 320 pages
ISBN-10 9781633430037
ISBN-13 978-1633430037
Item Weight 1.2 pounds (540 grams)
Dimensions 7.38 x 0.7 x 9.25 inches (18.7 x 1.8 x 23.5 cm)

แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ˜แƒก แƒแƒฆแƒฌแƒ”แƒ แƒ˜แƒšแƒแƒ‘แƒ

Introducing Data Science: Big Data, Machine Learning, and more, using Python tools

แƒ’แƒแƒฅแƒ•แƒ— แƒ แƒแƒ˜แƒ›แƒ” แƒจแƒ”แƒ™แƒ˜แƒ—แƒฎแƒ•แƒ? แƒ›แƒแƒ’แƒ•แƒ›แƒแƒ แƒ—แƒ”แƒ— แƒฉแƒแƒ—แƒจแƒ˜

แƒ›แƒแƒ›แƒฎแƒ›แƒแƒ แƒ”แƒ‘แƒ”แƒšแƒ—แƒ แƒ™แƒ˜แƒ—แƒฎแƒ•แƒ”แƒ‘แƒ˜ แƒ“แƒ แƒžแƒแƒกแƒฃแƒฎแƒ”แƒ‘แƒ˜

  • แƒ™แƒ˜แƒ—แƒฎแƒ•แƒ: แƒ แƒแƒ’แƒแƒ  แƒ•แƒ˜แƒงแƒ˜แƒ“แƒแƒ— Introducing Data Science: Big Data, Machine แƒแƒœแƒšแƒแƒ˜แƒœ Ubuy-แƒ“แƒแƒœ?

    แƒžแƒแƒกแƒฃแƒฎแƒ˜: แƒ›แƒแƒ แƒขแƒ˜แƒ•แƒ˜แƒ แƒงแƒ˜แƒ“แƒ•แƒ Introducing Data Science: Big Data, Machine แƒแƒœแƒšแƒแƒ˜แƒœ Ubuy-แƒ“แƒแƒœ.. แƒ—แƒฅแƒ•แƒ”แƒœ แƒฃแƒ‘แƒ แƒแƒšแƒแƒ“ แƒฃแƒœแƒ“แƒ แƒ›แƒแƒซแƒ”แƒ‘แƒœแƒแƒ— แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ˜, แƒแƒ˜แƒ แƒฉแƒ˜แƒแƒ— แƒ—แƒฅแƒ•แƒ”แƒœแƒ˜ แƒ›แƒ˜แƒฌแƒแƒ“แƒ”แƒ‘แƒ˜แƒก แƒ›แƒ”แƒ—แƒแƒ“แƒ˜ แƒจแƒ”แƒ›แƒแƒฌแƒ›แƒ”แƒ‘แƒ˜แƒก แƒ“แƒ แƒแƒก แƒ“แƒ แƒ›แƒ˜แƒ˜แƒขแƒแƒœแƒแƒ— แƒ˜แƒ’แƒ˜ แƒ—แƒฅแƒ•แƒ”แƒœแƒก แƒแƒ“แƒ’แƒ˜แƒšแƒแƒก.
  • แƒ™แƒ˜แƒ—แƒฎแƒ•แƒ: Introducing Data Science: Big Data, Machine แƒฎแƒ”แƒšแƒ›แƒ˜แƒกแƒแƒฌแƒ•แƒ“แƒแƒ›แƒ˜แƒ แƒแƒœแƒšแƒแƒ˜แƒœ แƒจแƒแƒžแƒ˜แƒœแƒ’แƒ˜แƒกแƒ—แƒ•แƒ˜แƒก Georgia-แƒจแƒ˜?

    แƒžแƒแƒกแƒฃแƒฎแƒ˜: แƒ“แƒ˜แƒแƒฎ, Ubuy Georgia-แƒจแƒ˜ แƒ”แƒก แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ˜ แƒ—แƒฅแƒ•แƒ”แƒœแƒ—แƒ•แƒ˜แƒก แƒฎแƒ”แƒšแƒ›แƒ˜แƒกแƒแƒฌแƒ•แƒ“แƒแƒ›แƒ˜แƒ แƒ’แƒแƒœแƒ˜แƒ•แƒ แƒฃแƒš แƒคแƒแƒกแƒแƒ“.. Introducing Data Science: Big Data, Machine แƒแƒ  แƒแƒ แƒ˜แƒก แƒฎแƒ”แƒšแƒ›แƒ˜แƒกแƒแƒฌแƒ•แƒ“แƒแƒ›แƒ˜ แƒแƒ“แƒ’แƒ˜แƒšแƒแƒ‘แƒ แƒ˜แƒ•แƒแƒ“, แƒ›แƒแƒ’แƒ แƒแƒ› แƒจแƒ”แƒ’แƒ˜แƒซแƒšแƒ˜แƒแƒ— แƒ’แƒ•แƒฏแƒ”แƒ แƒแƒ“แƒ”แƒก แƒฉแƒ•แƒ”แƒœแƒ˜ แƒ”แƒฅแƒกแƒžแƒ แƒ”แƒก แƒ›แƒ˜แƒฌแƒแƒ“แƒ”แƒ‘แƒ˜แƒก แƒกแƒ”แƒ แƒ•แƒ˜แƒกแƒ”แƒ‘แƒ˜.
  • แƒ™แƒ˜แƒ—แƒฎแƒ•แƒ: แƒ แƒแƒ›แƒ“แƒ”แƒœแƒ˜ แƒ“แƒ แƒ แƒกแƒญแƒ˜แƒ แƒ“แƒ”แƒ‘แƒ แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ˜แƒก แƒ›แƒ˜แƒฆแƒ”แƒ‘แƒแƒก แƒจแƒ”แƒ™แƒ•แƒ”แƒ—แƒ˜แƒก แƒ’แƒแƒคแƒแƒ แƒ›แƒ”แƒ‘แƒ˜แƒก แƒจแƒ”แƒ›แƒ“แƒ”แƒ’?

    แƒžแƒแƒกแƒฃแƒฎแƒ˜: แƒ—แƒฅแƒ•แƒ”แƒœแƒ˜ แƒจแƒ”แƒ™แƒ•แƒ”แƒ—แƒ˜แƒšแƒ˜ แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ˜แƒก แƒ›แƒ˜แƒฌแƒแƒ“แƒ”แƒ‘แƒ˜แƒก แƒ“แƒ แƒ แƒ’แƒแƒœแƒกแƒฎแƒ•แƒแƒ•แƒ“แƒ”แƒ‘แƒ แƒ—แƒฅแƒ•แƒ”แƒœ แƒ›แƒ˜แƒ”แƒ  แƒจแƒ”แƒ™แƒ•แƒ”แƒ—แƒ˜แƒšแƒ˜ แƒ“แƒ แƒ›แƒ˜แƒฌแƒแƒ“แƒ”แƒ‘แƒ˜แƒก แƒ›แƒ”แƒ—แƒแƒ“แƒ˜แƒก แƒ›แƒ˜แƒฎแƒ”แƒ“แƒ•แƒ˜แƒ—, แƒ แƒแƒ›แƒ”แƒšแƒ˜แƒช แƒแƒ แƒฉแƒ”แƒฃแƒšแƒ˜แƒ.. แƒ›แƒ˜แƒฌแƒแƒ“แƒ”แƒ‘แƒ˜แƒก แƒกแƒแƒ•แƒแƒ แƒแƒฃแƒ“แƒ แƒ“แƒ แƒ แƒ›แƒ˜แƒ—แƒ˜แƒ—แƒ”แƒ‘แƒฃแƒšแƒ˜แƒ แƒจแƒ”แƒ™แƒ•แƒ”แƒ—แƒ˜แƒก แƒžแƒ แƒแƒชแƒ”แƒกแƒจแƒ˜, แƒแƒกแƒ” แƒ แƒแƒ› แƒจแƒแƒžแƒ˜แƒœแƒ’แƒ˜แƒก แƒ“แƒ แƒแƒก แƒ˜แƒงแƒแƒ•แƒ˜แƒ— แƒฃแƒงแƒฃแƒ แƒแƒ“แƒฆแƒ”แƒ‘แƒ.

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  • แƒจแƒ”แƒ–แƒฆแƒฃแƒ“แƒ•แƒ”แƒ‘แƒ˜: แƒ’แƒ—แƒฎแƒแƒ•แƒ—, แƒ’แƒแƒ˜แƒ—แƒ•แƒแƒšแƒ˜แƒกแƒฌแƒ˜แƒœแƒแƒ—, แƒ แƒแƒ› แƒกแƒแƒ–แƒฆแƒ•แƒแƒ แƒ’แƒแƒ แƒ”แƒ— แƒ’แƒแƒ’แƒ–แƒแƒ•แƒœแƒ˜แƒšแƒ˜ แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ”แƒ‘แƒ˜แƒกแƒ—แƒ•แƒ˜แƒก แƒ›แƒฌแƒแƒ แƒ›แƒแƒ”แƒ‘แƒšแƒ˜แƒก แƒ’แƒแƒ แƒแƒœแƒขแƒ˜แƒ แƒจแƒ”แƒ˜แƒซแƒšแƒ”แƒ‘แƒ แƒแƒ  แƒ˜แƒงแƒแƒก แƒ›แƒแƒฅแƒ›แƒ”แƒ“แƒ˜; แƒ›แƒฌแƒแƒ แƒ›แƒแƒ”แƒ‘แƒšแƒ˜แƒก แƒ›แƒแƒ›แƒกแƒแƒฎแƒฃแƒ แƒ”แƒ‘แƒ˜แƒก แƒžแƒแƒ แƒแƒ›แƒ”แƒขแƒ แƒ”แƒ‘แƒ˜ แƒจแƒ”แƒ˜แƒซแƒšแƒ”แƒ‘แƒ แƒแƒ  แƒ˜แƒงแƒแƒก แƒฎแƒ”แƒšแƒ›แƒ˜แƒกแƒแƒฌแƒ•แƒ“แƒแƒ›แƒ˜; แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ˜แƒก แƒ˜แƒœแƒกแƒขแƒ แƒฃแƒฅแƒชแƒ˜แƒ”แƒ‘แƒ˜ แƒ“แƒ แƒฃแƒกแƒแƒคแƒ แƒ—แƒฎแƒแƒ”แƒ‘แƒ˜แƒก แƒ’แƒแƒคแƒ แƒ—แƒฎแƒ˜แƒšแƒ”แƒ‘แƒ”แƒ‘แƒ˜ แƒจแƒ”แƒ˜แƒซแƒšแƒ”แƒ‘แƒ แƒแƒ  แƒ˜แƒงแƒแƒก แƒ“แƒแƒœแƒ˜แƒจแƒœแƒฃแƒšแƒ”แƒ‘แƒ˜แƒก แƒฅแƒ•แƒ”แƒงแƒœแƒ˜แƒก แƒ”แƒœแƒแƒ–แƒ”; แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ”แƒ‘แƒ˜ (แƒ“แƒ แƒ›แƒแƒกแƒ—แƒแƒœ แƒ“แƒแƒ™แƒแƒ•แƒจแƒ˜แƒ แƒ”แƒ‘แƒฃแƒšแƒ˜ แƒ›แƒแƒกแƒแƒšแƒ”แƒ‘แƒ˜) แƒจแƒ”แƒ˜แƒซแƒšแƒ”แƒ‘แƒ แƒแƒ  แƒ˜แƒงแƒแƒก แƒจแƒ”แƒ›แƒฃแƒจแƒแƒ•แƒ”แƒ‘แƒฃแƒšแƒ˜ แƒ“แƒแƒœแƒ˜แƒจแƒœแƒฃแƒšแƒ”แƒ‘แƒ˜แƒก แƒฅแƒ•แƒ”แƒงแƒœแƒ˜แƒก แƒกแƒขแƒแƒœแƒ“แƒแƒ แƒขแƒ”แƒ‘แƒ˜แƒก, แƒกแƒžแƒ”แƒชแƒ˜แƒคแƒ˜แƒ™แƒแƒชแƒ˜แƒ”แƒ‘แƒ˜แƒกแƒ แƒ“แƒ แƒ›แƒแƒ แƒ™แƒ˜แƒ แƒ”แƒ‘แƒ˜แƒก แƒ›แƒแƒ—แƒฎแƒแƒ•แƒœแƒ”แƒ‘แƒ˜แƒก แƒจแƒ”แƒกแƒแƒ‘แƒแƒ›แƒ˜แƒกแƒแƒ“; แƒ“แƒ แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ”แƒ‘แƒ˜ แƒจแƒ”แƒ˜แƒซแƒšแƒ”แƒ‘แƒ แƒแƒ  แƒจแƒ”แƒ”แƒกแƒแƒ‘แƒแƒ›แƒ”แƒ‘แƒแƒ“แƒ”แƒก แƒ“แƒแƒœแƒ˜แƒจแƒœแƒฃแƒšแƒ”แƒ‘แƒ˜แƒก แƒฅแƒ•แƒ”แƒงแƒœแƒ˜แƒก แƒซแƒแƒ‘แƒ•แƒ˜แƒกแƒ แƒ“แƒ แƒกแƒฎแƒ•แƒ แƒ”แƒšแƒ”แƒฅแƒขแƒ แƒ แƒกแƒขแƒแƒœแƒ“แƒแƒ แƒขแƒ”แƒ‘แƒก (แƒกแƒแƒญแƒ˜แƒ แƒแƒ”แƒ‘แƒ˜แƒก แƒจแƒ”แƒ›แƒ—แƒฎแƒ•แƒ”แƒ•แƒแƒจแƒ˜ แƒกแƒแƒญแƒ˜แƒ แƒแƒ แƒแƒ“แƒแƒžแƒขแƒ”แƒ แƒ˜ แƒแƒœ แƒ’แƒแƒ“แƒแƒ›แƒงแƒ•แƒแƒœแƒ˜). แƒ›แƒ˜แƒ›แƒฆแƒ”แƒ‘แƒ˜ แƒžแƒแƒกแƒฃแƒฎแƒ˜แƒกแƒ›แƒ’แƒ”แƒ‘แƒ”แƒšแƒ˜แƒ แƒฃแƒ–แƒ แƒฃแƒœแƒ•แƒ”แƒšแƒงแƒแƒก, แƒ แƒแƒ› แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ˜ แƒ™แƒแƒœแƒแƒœแƒ˜แƒ”แƒ แƒแƒ“ แƒจแƒ”แƒ›แƒแƒ˜แƒขแƒแƒœแƒแƒก แƒ“แƒแƒœแƒ˜แƒจแƒœแƒฃแƒšแƒ”แƒ‘แƒ˜แƒก แƒฅแƒ•แƒ”แƒงแƒแƒœแƒแƒจแƒ˜. Ubuy-แƒก แƒแƒœ แƒ›แƒ˜แƒกแƒ˜ แƒแƒคแƒ˜แƒšแƒ˜แƒ แƒ”แƒ‘แƒฃแƒšแƒ˜ แƒžแƒ˜แƒ แƒ”แƒ‘แƒ˜แƒก แƒ›แƒ”แƒจแƒ•แƒ”แƒแƒ‘แƒ˜แƒ— แƒจแƒ”แƒ™แƒ•แƒ”แƒ—แƒ˜แƒกแƒแƒก แƒ›แƒ˜แƒ›แƒฆแƒ”แƒ‘แƒ˜ แƒแƒ แƒ˜แƒก แƒ แƒ”แƒ’แƒ˜แƒกแƒขแƒ แƒ˜แƒ แƒ”แƒ‘แƒฃแƒšแƒ˜ แƒ˜แƒ›แƒžแƒแƒ แƒขแƒ˜แƒแƒ แƒ˜ แƒ“แƒ แƒ›แƒแƒœ แƒฃแƒœแƒ“แƒ แƒ’แƒแƒ˜แƒ—แƒ•แƒแƒšแƒ˜แƒกแƒฌแƒ˜แƒœแƒแƒก แƒ“แƒแƒœแƒ˜แƒจแƒœแƒฃแƒšแƒ”แƒ‘แƒ˜แƒก แƒฅแƒ•แƒ”แƒงแƒœแƒ˜แƒก แƒงแƒ•แƒ”แƒšแƒ แƒ™แƒแƒœแƒแƒœแƒ˜ แƒ“แƒ แƒ“แƒ”แƒ‘แƒฃแƒšแƒ”แƒ‘แƒ.
  • Ubuy-แƒ–แƒ” แƒฉแƒแƒ›แƒแƒ—แƒ•แƒšแƒ˜แƒšแƒ˜ แƒงแƒ•แƒ”แƒšแƒ แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ˜ แƒแƒ  แƒแƒ แƒ˜แƒก แƒ’แƒแƒงแƒ˜แƒ“แƒ•แƒแƒจแƒ˜, แƒ แƒแƒ“แƒ’แƒแƒœ Ubuy แƒแƒ แƒ˜แƒก แƒ’แƒšแƒแƒ‘แƒแƒšแƒฃแƒ แƒ˜ แƒกแƒแƒซแƒ˜แƒ”แƒ‘แƒ แƒกแƒ˜แƒกแƒขแƒ”แƒ›แƒ แƒ“แƒ แƒžแƒ แƒแƒ“แƒฃแƒฅแƒขแƒ”แƒ‘แƒ˜ แƒ”แƒฅแƒ•แƒ”แƒ›แƒ“แƒ”แƒ‘แƒแƒ แƒ”แƒ‘แƒ แƒกแƒแƒ”แƒฅแƒกแƒžแƒแƒ แƒขแƒ/แƒกแƒแƒ•แƒแƒญแƒ แƒ แƒ แƒ”แƒ’แƒฃแƒšแƒแƒชแƒ˜แƒ”แƒ‘แƒก.

GEL 178

แƒจแƒ”แƒฃแƒ™แƒ•แƒ”แƒ—แƒ”แƒ— แƒแƒฎแƒšแƒแƒ•แƒ” แƒ“แƒ แƒ›แƒ˜แƒ˜แƒฆแƒ”แƒ— แƒแƒ—แƒฎแƒจแƒแƒ‘แƒแƒ—แƒ˜, แƒแƒฅแƒขแƒแƒ›แƒ‘แƒ”แƒ แƒ˜ 07

QTY:

แƒ›แƒแƒ แƒแƒ’แƒจแƒ˜ แƒ“แƒแƒ แƒฉแƒ”แƒœแƒ˜แƒšแƒ˜แƒ แƒ›แƒฎแƒแƒšแƒแƒ“ 3 แƒ”แƒ แƒ—แƒ”แƒฃแƒšแƒ˜.
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